Robust transmission expansion planning (TEP) applying shrinkage

Stochastic optimization finds the best solution in terms of expected cost for a given scenario tree, but the definition of this tree is often incomplete or subjective. In these cases, it is desirable to make the solution robust with respect to small changes in the definition of scenarios. We propose to shrink the stochastic solution towards a robust benchmark, this is, modify it to make it is more similar to another TEP solution which is calculated independently from the scenario tree. A case study illustrates the method.